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Titolo: Relative fuzzy connectedness among multiple objects: Theory, algorithms, and applications in image segmentation
Autore: Saha, PK; Udupa, JK;
 Indirizzi:
 Univ Penn, Dept Radiol, Med Image Proc Grp, Philadelphia, PA 19104 USA Univ Penn Philadelphia PA USA 19104 Proc Grp, Philadelphia, PA 19104 USA
 Titolo Testata:
 COMPUTER VISION AND IMAGE UNDERSTANDING
fascicolo: 1,
volume: 82,
anno: 2001,
pagine: 42  56
 SICI:
 10773142(200104)82:1<42:RFCAMO>2.0.ZU;2P
 Fonte:
 ISI
 Lingua:
 ENG
 Soggetto:
 QUANTIFICATION; EXTRACTION; DEFINITION;
 Keywords:
 fuzzy connectedness; image segmentation; object definition; digital topology;
 Tipo documento:
 Article
 Natura:
 Periodico
 Settore Disciplinare:
 Engineering, Computing & Technology
 Citazioni:
 25
 Recensione:
 Indirizzi per estratti:
 Indirizzo: Saha, PK Univ Penn, Dept Radiol, Med Image Proc Grp, 4th Floor,Blockley Hall,423 Guardian Dr, Philadelphia, PA 19104 USA Univ Penn 4th Floor,BlockleyHall,423 Guardian Dr Philadelphia PA USA 19104



 Citazione:
 P.K. Saha e J.K. Udupa, "Relative fuzzy connectedness among multiple objects: Theory, algorithms, and applications in image segmentation", COMP VIS IM, 82(1), 2001, pp. 4256
Abstract
The notion of fuzzy connectedness captures the idea of "hangingtogetherness" of image elements in an object by assigning a strength of connectednessto every possible path between every possible pair of image elements. Thisconcept leads to powerful image segmentation algorithms based on dynamic programming whose effectiveness has been demonstrated on thousands of imagesin a variety of applications. In a previous framework, we introduced the notion of relative fuzzy connectedness for separating a foreground object from a background object. In this framework, an image element c is consideredto belong to that among these two objects with respect to whose reference image element c has the higher strength of connectedness. In fuzzy connectedness, a local fuzzy relation called affinity is used on the image domain. This relation was required for theoretical reasons to be of fixed form in the previous framework. In the present paper, we generalize relative connectedness to multiple objects, allowing all objects (of importance) to competeamong themselves to grab membership of image elements based on their relative strength of connectedness to reference elements. We also allow affinityto be tailored to the individual objects. We present a theoretical and algorithmic framework and demonstrate that the objects defined are independentof the reference elements chosen as long as they are not in the fuzzy boundary between objects. Examples from medical imagine are presented to illustrate visually the effectiveness of multiple object relative fuzzy connectedness, A quantitative evaluation based on 160 mathematical phantom images demonstrates objectively the effectiveness of relative fuzzy connectedness with objecttailored affinity relation. (C) 2001 Academic Press.
ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 22/01/20 alle ore 07:04:14